The objective of this work is to uncover the determinants of specificity in G protein-coupled receptors (GPCRs). These receptors and the pathways controlled by them are the sites of action of more drugs than any other class of pathways. The approach marries computation with experiment and relies on a novel sequence analysis strategy developed by the PI, that uses phylogenetic trees to identify functionally important residues in proteins. The hypotheses to be tested are that (1) by providing a vast number of evolutionary mutations and assays that would otherwise remain untapped, this Evolutionary Trace strategy (ET) will allow us to identify signal transduction determinants in GPCRs. These determinants in turn should reveal (2) a universal on-off transmembrane conformational switch that controls G protein activation and, (3), distinct binding sites and relay pathways that are specific to the each receptors' precise ligand and G protein(s). These hypotheses will be tested first against the vast body of GPCR mutations already available from the literature, and second through targeted mutations in rhodopsin that aim to predictably change ligand and G protein coupling specificity. Specifically, Aim 1 is to develop the computational strategy and computational tools to apply this Evolutionary Trace strategy to GPCRs on a large-scale. Aim 2 is to identify computationally the determinants of ligand induced signaling in the transmembrane domain, followed by experimental validation through the literature and direct experiments in rhodopsin. Aim 3 is to identify the determinant of G protein coupling and specificity, followed by experimental validation as above. [unreadable] [unreadable] Thus we propose an integrated strategy to study the evolution of sequence, structure and function in GPCRs, closely coupled with experimental proof of principle in rhodopsin. In addition to the important insight into the molecular basis of GPCR function, and of drug activity that these studies should provide, development of an efficient, rational, and general strategy to guide experiments in GPCR would be a significant contribution to an important and difficult problem. [unreadable] [unreadable]